Bohyeon An

Korea Institute of Machinery & Materials

Papers

Total Citations

H-Index

About

Bohyeon An is a researcher at the forefront of intelligent robotic prosthetics, specializing in the integration of deep learning and computer vision to restore dexterous hand function for amputees. An’s core contributions lie in developing autonomous control systems that enable robotic prosthetic hands to intelligently perceive and interact with their environment. In their most cited work, “Grasping Time and Pose Selection for Robotic Prosthetic Hand Control Using Deep Learning Based Object Detection” (2022, 9 citations), An pioneered a method for a prosthetic hand to not only identify a target object from visual input but also to automatically determine the optimal grasping pose and timing—a critical step toward natural, intuitive prosthetic use. This builds on foundational research from 2020, which established a framework for selecting grasping targets using image-based deep learning, addressing the challenge of automatically choosing the appropriate operation among various grasping patterns. An’s work directly tackles a key limitation in modern prosthetics: the need for seamless, real-time adaptation to diverse objects. By fusing object detection with grasp planning, An is helping to bridge the gap between human intent and machine action, significantly improving the quality of life for hand amputees. Their research represents a vital advance in bioengineering and assistive robotics.